In this section
Attribution models provide a set of rules that allow assigning a specific value to the channels a user has interacted with before making the final conversion, thereby enabling the evaluation of each channel’s effectiveness in marketing campaigns.
Objectives
- Analyze the conversion rate per channel and cost per advertising campaign.
- Understand the paths users take before a final conversion.
- Gain insight into the media that generates greater interest among potential customers.
Each year, marketing teams across various companies invest a considerable amount of money in advertising campaigns. Among all the services used, some channels prove more effective at acquiring new customers. However, the number of interactions that occur before the final conversion makes this analysis complex. Therefore, it is important to use mathematical algorithms capable of performing this task.
What we do
Based on the data obtained from the paths followed to achieve a conversion, we apply different models that distribute the value of this conversion among the various channels the user interacts with.
How we do it
Understanding what a conversion is
Each marketing team has its own defined conversion. A conversion can be a purchase, sending a message through the website’s contact options, a certain number of clicks, etc.
Analysis, collection, and transformation of specific data
It is essential to obtain the paths that different users have followed before making a conversion.
We apply various mathematical models to the data, which automatically distribute the conversion value among the considered channels.
Discussion of results
Each mathematical model applies a set of rules that yield a different value. It is necessary to discuss the results with the marketing team to evaluate which model best suits their needs.